# Generative Embodied Multiple Behavior Control Systems for Human-like Agents

arXiv: https://arxiv.org/abs/2609.22691 · HTML: https://mlsanity.com/paper/2609.22691/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 30 of its 72 references that are in the map.
- First posted on arXiv 19 Sep 2026.

## Builds on (most cited first, 30 of 30)

- [Generative Agents: Interactive Simulacra of Human Behavior](https://mlsanity.com/paper/2304.03442/) (2023)
- [Cognitive Architectures for Language Agents](https://mlsanity.com/paper/2309.02427/) (2023)
- [OmniControl: Control Any Joint at Any Time for Human Motion Generation](https://mlsanity.com/paper/2310.08580/) (2023)
- [Large Language Models as Commonsense Knowledge for Large-Scale Task Planning](https://mlsanity.com/paper/2305.14078/) (2023)
- [HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes](https://mlsanity.com/paper/2210.09729/) (2022)
- [Scaling Up Dynamic Human-Scene Interaction Modeling](https://mlsanity.com/paper/2403.08629/) (2024)
- [Synthesizing Physical Character-Scene Interactions](https://mlsanity.com/paper/2302.00883/) (2023)
- [EgoLife: Towards Egocentric Life Assistant](https://mlsanity.com/paper/2503.03803/) (2025)
- [Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling](https://mlsanity.com/paper/2301.12050/) (2023)
- [Humanoid Agents: Platform for Simulating Human-like Generative Agents](https://mlsanity.com/paper/2310.05418/) (2023)
- [Human-Object Interaction from Human-Level Instructions](https://mlsanity.com/paper/2406.17840/) (2024)
- [Diffusion Self-Distillation for Zero-Shot Customized Image Generation](https://mlsanity.com/paper/2411.18616/) (2024)
- [Pre-training Contextualized World Models with In-the-wild Videos for Reinforcement Learning](https://mlsanity.com/paper/2305.18499/) (2023)
- [Kimodo: Scaling Controllable Human Motion Generation](https://mlsanity.com/paper/2603.15546/) (2026)
- [Multi-agent Embodied AI: Advances and Future Directions](https://mlsanity.com/paper/2505.05108/) (2025)
- [Simulating Human-like Daily Activities with Desire-driven Autonomy](https://mlsanity.com/paper/2412.06435/) (2024)
- [WANDR: Intention-guided Human Motion Generation](https://mlsanity.com/paper/2404.15383/) (2024)
- [Reinforcement World Model Learning for LLM-based Agents](https://mlsanity.com/paper/2602.05842/) (2026)
- [Virtual Community: An Open World for Humans, Robots, and Society](https://mlsanity.com/paper/2508.14893/) (2025)
- [Affordable Generative Agents](https://mlsanity.com/paper/2402.02053/) (2024)
- [AFSPP: Agent Framework for Shaping Preference and Personality with Large Language Models](https://mlsanity.com/paper/2401.02870/) (2024)
- [Bridging the Agent-World Gap: Text World Models for LLM-based Agents](https://mlsanity.com/paper/2606.09032/) (2026)
- [AgentSense: Virtual Sensor Data Generation Using LLM Agents in Simulated Home Environments](https://mlsanity.com/paper/2506.11773/) (2025)
- [Ella: Embodied Social Agents with Lifelong Memory](https://mlsanity.com/paper/2506.24019/) (2025)
- [InfBaGel: Human-Object-Scene Interaction Generation with Dynamic Perception and Iterative Refinement](https://mlsanity.com/paper/2604.04843/) (2026)
- [TSTMotion: Training-free Scene-aware Text-to-motion Generation](https://mlsanity.com/paper/2505.01182/) (2025)
- [Beyond Self-Interest: Modeling Social-Oriented Motivation for Human-like Multi-Agent Interactions](https://mlsanity.com/paper/2603.13890/) (2026)
- [Context-Value-Action Architecture for Value-Driven Large Language Model Agents](https://mlsanity.com/paper/2604.05939/) (2026)
- [Visually-grounded Humanoid Agents](https://mlsanity.com/paper/2604.08509/) (2026)
- [HabitAction: A Video Dataset for Human Habitual Behavior Recognition](https://mlsanity.com/paper/2408.13463/) (2024)

## Abstract (arXiv)

Building human-like agents that reproduce human behavior in realistic 3D environments has been a longstanding objective in AI. Existing human-like agent frameworks primarily focus on modeling goal-directed behavior. However, cognitive neuroscience commonly believes that human behaviors are more likely controlled by multiple control systems, including goal-directed and habitual behavior control systems. Habitual behavior has been largely overlooked though it plays a crucial role in human daily life. In this paper, we address this gap by proposing a multiple control systems setup that jointly models goal-directed and habitual behaviors. Building on this setup, we propose GEMS, in which the Habitual Controller retrieves habitual actions from habit memory in response to relevant environmental stimuli, while the Goal-directed Controller proposes goal-directed actions and estimates their values. The Arbiter dynamically governs the relative influence of each controller and selects the final action. To construct diverse human-level behavior instructions in 3D environments, we further develop a keyframe-guided motion generation module. Extensive quantitative evaluations, human and ablation studies demonstrate that human-likeness performance is substantially improved by GEMS. The efficacy of GEMS indicates the benefits of leveraging habitual behavior and multiple behavior control system coordination for believable embodied human-like agents. The code is available at hrefhttps://anonymous.4open.science/r/review-video-82f4/demo.mp4this link.